We have found ourselves in the 4th industrial revolution in history, and this time, we have transitioned into the cyber-physical world. Since the inception of computers more than two decades ago, we have developed one technological innovation after another. From massive computers that would encompass entire floors of buildings, to personal computers that fit in our pockets with more processing power than their predecessors, technology is advancing at a whirlwind pace. Business technology has been advancing at the same speed, as people have always found new ways to apply new technology to the business world. The latest case of this phenomenon is called Intelligent Automation.
Currently, as with all new technology, financial firms are a bit hesitant to fully commit to using intelligent automation. The mindset that many companies possess right now is that intelligent automation is best used as a cost-cutting measure. While intelligent automation certainly does cut costs, it also presents the opportunity for extreme growth. So why aren’t more companies investing in this? It is important to understand what intelligent automation is before dissecting that question any further.
Intelligent automation is actually the summation of a few different types of cutting edge technology working together. While useful by themselves, these technologies prove to be even more effective when combined and working together.
One of the main components is RPA, or Robot Processing Automation, which allows for “software bots” to record the actions of a human counterpart and mimic those actions on their own. However, RPA is limited in that it is only able to complete tasks that it “sees” a person does.
This is where Machine Learning comes into play. Machine Learning is a system that is able to discover different patterns in data, and thus learn from these different patterns to make predictions. Not only can ML make predictions, but it can also provide insight about patterns that it discovers.
Another important segment of intelligent automation is Smart Workflow technology, which when used is able to manage and organize the work done by both bots and humans. This ensures that the transition between work from robot-to-human and from human-to-robot is seamless.
The final components of intelligent automation are Natural Language Processing and cognitive agents, technology that makes it possible for a computer to recognize human language in real-time.
When it comes to the adoption of intelligent automation, the process has been slow. Automation has already been getting a significant foothold in the finance industry for some time, but many people worry that the technology will take away much of what they do, and eventually replace them and their job wholly. However, intelligent automation isn’t anywhere close to being able to fully replace a human, but can greatly improve the efficiency of an organization.
Intelligent automation can be utilized in many ways in the finance industry. Different firms in different niches within it have found different uses for it. For example, a hedge fund who has human analysts write notes on what is happening in the market. Instead of having other humans analyze and fact check hundreds of thousands of pages of notes, the hedge fund can deploy bots to do the same task, but more accurately and much faster.
Other companies, an insurance company for example, deal with thousands of queries from customers about their policy and about incidents that have occurred. A company can institute intelligent automation within their infrastructure to create a chat bot system that can redirect the queries from the customers to the proper departments within the company.
According to Capgemini, companies that have invested in this technology have seen a 2%-5% increase in topline growth. This begs the same question posed earlier, why doesn’t every company invest in this technology?
Unfortunately, there are a few things that are preventing intelligent automation from taking off. Intelligent automation is expensive to implement in a company at first, and it takes a while to see an investment in intelligent automation to pay dividends. This gives credence to some of the reluctance of many finance executives, as intelligent automation can be seen as more of long-term play, and most organizations want results up front.
The biggest roadblock in expanding the use of intelligent automation in the finance industry is that too few companies are considering it as an option. Companies too often conduct tests of intelligent automation without understanding the full scope of how useful the technology could be, and thus aren’t sure what they want out of the tests they’re running. If a company plans on using intelligent automation, it is important that they have an outlook on what they hope to achieve with the use of intelligent automation. Once a plan is decided upon, tests should be conducted to see if the desired result is achievable. After that, all it takes is getting employees on board, a full commitment to scaling the technology throughout the company, and time to truly evaluate intelligent automation.
Intelligent automation has the ability to reduce the cost of operation while meeting the needs to digital-savvy consumers for not only the finance industry, but industries across the board. While it is not there to replace jobs, firms that take the steps to integrate intelligent automation into their business processes will inevitably benefit from the combination of robotic efficiency with human awareness.